Results 21 to 30 of about 65,767 (202)
Quantum medical images processing foundations and applications
IET Quantum Communication, Volume 3, Issue 4, Page 201-213, December 2022., 2022 Abstract Medical imaging is considered one of the most important areas within scientific imaging due to the rapid and ongoing development in computer‐aided medical image visualisation, advances in analysis approaches, and computer‐aided diagnosis.
Ahmed Elaraby
wiley +1 more source
Mini-DDSM: Mammography-based Automatic Age Estimation [PDF]
, 2020 Age estimation has attracted attention for its various medical applications. There are many studies on human age estimation from biomedical images. However, there is no research done on mammograms for age estimation, as far as we know. The purpose of this study is to devise an AI-based model for estimating age from mammogram images.
arxiv +1 more source
M&M: Tackling False Positives in Mammography with a Multi-view and Multi-instance Learning Sparse Detector [PDF]
arXiv, 2023 Deep-learning-based object detection methods show promise for improving screening mammography, but high rates of false positives can hinder their effectiveness in clinical practice. To reduce false positives, we identify three challenges: (1) unlike natural images, a malignant mammogram typically contains only one malignant finding; (2) mammography ...
arxiv
Universal Hydrogel Carrier Enhances Bone Graft Success: Preclinical and Clinical Evaluation
Advanced Healthcare Materials, EarlyView.TX hydrogel improves the delivery of different types of particulate bone grafts, maintaining them at the implantation sites, and resulting in favorable bone regenerative outcomes. Abstract Orthopedic, maxillofacial, and complex dentoalveolar bone grafting procedures that require donor‐site bone harvesting can be associated with post‐surgical ...
Dax Calder +9 more
wiley +1 more source
Descriptive analysis of computational methods for automating mammograms with practical applications [PDF]
arXiv, 2020 Mammography is a vital screening technique for early revealing and identification of breast cancer in order to assist to decrease mortality rate. Practical applications of mammograms are not limited to breast cancer revealing, identification ,but include task based lens design, image compression, image classification, content based image retrieval and ...
arxiv
A New Computer-Aided Diagnosis System with Modified Genetic Feature Selection for BI-RADS Classification of Breast Masses in Mammograms [PDF]
, 2020 Mammography remains the most prevalent imaging tool for early breast cancer screening. The language used to describe abnormalities in mammographic reports is based on the breast Imaging Reporting and Data System (BI-RADS). Assigning a correct BI-RADS category to each examined mammogram is a strenuous and challenging task for even experts.
arxiv +1 more source
Green Fabrication of Sulfonium‐Containing Bismuth Materials for High‐Sensitivity X‐Ray Detection
Advanced Materials, EarlyView.[(CH3CH2)3S]6Bi8I30 and [[(CH3CH2)3S]AgBiI5 are introduced as novel X‐ray detector materials with exceptional sensitivity and low detection limits. Produced via scalable, green synthesis, they remain highly durable after 9 months of storage and continuous X‐ray use, setting a new benchmark for medical imaging and outperforming many existing and ...
Allan Starkholm +11 more
wiley +1 more source
Advanced Science, EarlyView.Following a comparative analysis of omics‐based cancer detection models, a novel liquid biopsy‐based multi‐omics combined model is developed for the early detection of gynecological malignancies. By integrating cell‐free DNA methylation and tumor protein markers, the combined model demonstrates high specificity and sensitivity and is uniquely designed ...
Zheng Feng +17 more
wiley +1 more source
Diagnostic performance of radiologists with and without different CAD systems for mammography [PDF]
, 2003 The purpose of this study is the evaluation of the variation of performance in terms of sensitivity and specificity of two radiologists with different experience in mammography, with and without the assistance of two different CAD systems. The CAD considered are SecondLookTM (CADx Medical Systems, Canada), and CALMA (Computer Assisted Library in ...
arxiv +1 more source
IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography [PDF]
arXiv, 2021 Interpretability in machine learning models is important in high-stakes decisions, such as whether to order a biopsy based on a mammographic exam. Mammography poses important challenges that are not present in other computer vision tasks: datasets are small, confounding information is present, and it can be difficult even for a radiologist to decide ...
arxiv